Question 241: Although machine learning is useful, there are barriers to implementation. What is one common obstacle faced by businesses looking to use machine learning tools?
A. Not enough data to perform machine learning processes.
B. Lack of data science skills or data scientists.
C. No need for the big analytics processing power in machine learning programs.
Correct Answer: B. Lack of data science skills or data scientists.
Explanation: Putting machine learning and AI tools into use isn’t easy. It requires a lot of expertise in data preparation, modeling and data science — skills that can be few and far between in many organizations. Skills in deploying big data platforms are also in short supply. That often leaves companies looking to implement and use machine learning technologies with citizen data scientists and automated tools.
Question 242: Which of the following is a technique frequently used in machine learning and AI programs?
A. Classification of data into categories based on attributes.
B. Grouping similar objects into clusters of related events or topics.
C. Identifying relationships between events to predict when one will follow the other.
D. All of the above are common machine learning techniques.
Correct Answer: D. All of the above are common machine learning techniques.
Explanation: Machine learning algorithms are what data scientists use to build predictive models and to analyze data. While many types of algorithms are used in machine learning and AI applications, classification, clustering and affinity analysis algorithms are three of the most common ones.
Question 243: True or False: Machine learning is prone to bias due to black box AI systems.
A. True
B. False
Correct Answer: A. True
Explanation: One of the biggest drawbacks to implementing machine learning is algorithms’ propensity toward bias. From approving more elderly applicants for certain loans to burying female resumes, AI bias has long been a source of stress for enterprises. As such a pervasive issue, companies are now deploying programs, tools and training modifications to reduce bias.